Traumatic injuries are the leading cause of hospitalization among
Active Duty military personnel [1]. Injuries are also a leading
diagnosis among veterans of Operation Iraqi Freedom/Operation Enduring
Freedom (OIF/OEF) seeking care in the Veterans Health Administration
(VHA) healthcare system [2]. Interestingly, studies have shown that
veterans who have been deployed are at greater risk of fatal injuries
following deployment than veterans from the same military service era
who were not deployed [3-4]. Since the beginning of OIF/OEF, the VHA has
been treating an increasing number of veterans

with traumatic injuries incurred during or after their military
service. To meet the needs of these patients, the VHA created the
Polytrauma System of Care, which includes 4 regional Polytrauma
Rehabilitation Centers (PRCs) that provide inpatient care, 22 Polytrauma
Network Sites that specialize in outpatient rehabilitation programs,
multidisciplinary polytrauma teams at smaller VHA facilities, and
designated points of contact at all other VHA facilities [5]. Most
patients treated in the PRCs have sustained a traumatic brain injury
(TBI) in combination with other injuries that have led to significant
impairments [6-7]. To date, there has been no systematic study of the
etiology of these patients' injuries, such as the proportion
related to different forms of combat or the proportion related to
postdeployment motor vehicle crashes. As Scott et al. and Belanger et
al. have argued, such information has implications for clinical service
delivery [8-9]. For example, knowledge of injury mechanism can prompt
systematic screenings for sequelae or comorbidities commonly associated
with the particular source of injury. Knowledge of injury etiology is
also critical for development of post-deployment injury prevention
efforts.

Details on the etiology of injuries treated within VHA can be
collected through a comprehensive review of an individual patient's
chart notes. This process requires access to the Computerized Patient
Record System, the VHA's electronic medical record system, and is
laborious if not time-prohibitive for understanding injury trends in
large patient populations. An alternative, more efficient approach to
collecting information on injuries treated in the VHA is the use of
administrative data. The International Classification of Diseases-9th
Revision-Clinical Modification (ICD-9-CM) coding manual includes a
supplemental set of codes called "E-codes" (short for
"external cause-of-injury codes") that are specific to
traumatic injury [10] and are included in VHA administrative data.
E-codes (codes E800.0-E999.9) were developed for injury surveillance
[11] and are to be assigned whenever one or more ICD-9-CM injury
diagnosis code (codes 800.00-999.9) is applied to a patient record
[12-13]. Additionally, E-codes should be assigned to any other condition
outside this range that is due to an external cause [12].

While diagnosis codes provide information on the anatomical nature
of injuries (type and body region[s] involved), E-codes provide details
on the source (e.g., blast/explosion, motor vehicle, fall), intent
(unintentional, self-inflicted, assault), and circumstances (e.g.,
handgun vs rifle, driver vs passenger) of injury events. Additional
E-codes indicate place of occurrence (e.g., home, public building) of
the injury. The source and intent of injury are usually captured by the
first three digits of an E-code. However, similar to diagnosis codes,
E-codes can be up to five digits in length, with the fourth and fifth
digits identifying the more specific circumstances of an injury event.
For example, E991 represents an injury due to war operations by bullets
and fragments, while E991.3 specifies that the fragments were due to an
antipersonnel bomb. Also similar to diagnosis codes, "late
effects" E-codes exist for identifying medical encounters relevant
to the late effects or sequelae of an injury and are to be used whenever
a late effects diagnosis code is assigned. For example, a veteran
seeking treatment for postconcussive symptoms due to a blast-related TBI
experienced in theater might be assigned a late effects diagnosis code
of 907.0 ("late effect of intracranial injury without skull
fracture") along with a late effects E-code of E999.0 ("late
effect of injury due to war operations"). Multiple E-codes may be
assigned when more than one distinct source of injury is noted or when
multiple E-codes are necessary to describe complete details of a single
source of injury. For example, an injury scenario in which an explosive
device detonated underneath a vehicle would potentially be assigned
E-codes from both the war operations and motor vehicle categories. A
coding hierarchy exists such that certain injury sources (abuse,
terrorism, cataclysmic events, and transport [i.e., motor vehicle]
events) are prioritized and are to be coded first. We refer the reader
to the Centers for Disease Control and Prevention Official Guidelines,
available online, for further information on these and additional coding
rules [12].

Medical records technicians with specialty training (typically a
2-year degree and certification) assign codes to VHA inpatient medical
records within 14 days after patient discharge. The VHA maintains both
rigorous qualification standards for medical records technicians and a
comprehensive system of data validation for coding completeness and
accuracy [14]. To our knowledge, no published scientific studies have
examined the accuracy of E-coding within VHA, although one 2005 report
stated that pilot studies were underway [15]. Rates of E-coding of
injury-related hospitalization discharges in community hospitals vary
across state systems and range from just over half to nearly 100 percent
[16-17]. Studies examining the compliance and accuracy of E-coding in
U.S. hospital discharge data [17-21] and emergency department electronic
data [21-23] have shown wide variation in practices, with some systems
providing relatively complete and accurate E-codes when compared with
patient chart notes as the gold standard (GS) [20]. If E-coding for VHA
patients were shown to be accurate, these data could be used to
efficiently identify and enumerate mechanisms, intent, and circumstances
of injuries being treated in the VHA system of care. The purpose of this
study was to conduct a preliminary examination of E-coding practice and
accuracy with use of a population of PRC inpatients.

METHODS

Overview

This study was based on data for 566 patients consecutively treated
at any one of the four VHA PRC sites between October 2001 and January
2006. Data for PRC patients were extracted from Vista (Veterans Health
Information System and Technology Architecture) and included patient
characteristics, chart notes, principal diagnosis code, and additional
ICD-9-CM diagnosis and E-codes entered into 1 of 13 available fields.
This was a secondary analysis of data collected as part of a study to
characterize the injuries and impairments of PRC patients wounded in
combat [24].

While most veterans and servicemembers treated at the PRCs have
sustained traumatic injuries, a small minority of patients are admitted
to the PRCs after a stroke or other neurological condition. Similar to
other E-code studies [17,20,23,25], our approach was to identify
patients who were treated for injuries and assign E-codes to these
patients based on expert review of their medical records. We then
assessed VHA E-coding accuracy based on the results of this review. Also
consistent with other E-code studies, our focus was on selecting the
single most appropriate source-of-injury E-code for each injury event,
rather than selecting multiple E-codes, such as those identifying places
of occurrence.

Gold Standard E-coding

Using the process followed by VHA coders, we conducted a detailed
review of patients' History & Physical and Discharge Summary
chart notes to identify PRC patients who were treated for externally
caused injuries and to establish GS E-codes for those stays. Our GS team
of coders was blinded to E-codes assigned by VHA coders during this
process. The team included the principal investigator, who is an injury
epidemiologist with experience in E-coding, and a certified medical
records coder contracted through an external agency for purposes of this
study. Each team member independently assigned E-codes to each
appropriate record by using standards from the ICD-9-CM codebook [10]
and coding guidelines [12], as well as VHA coding guidelines [13].
E-codes were then cross-validated for each record, with nonmatches (52%)
being reconciled through discussion and consensus. Almost all GS
nonmatches were at the third through fifth digits, representing the more
specific details of injury events.

Measures

Administrative data were used for analysis of patient demographic
characteristics, while GS E-codes were used to summarize sources of
patients' injuries. Because the focus of this study was on the
potential utility of E-codes for identifying etiology of patients'
injuries (rather than more specific circumstances of injury events), we
collapsed E-codes into broad source-of-injury categories representing
major sections of the E-code system. These categories were motor
vehicles (E810.0-E825.9, E929.0-E929.1, E988.5); falls (E833.0-E835.9,
E843.x, E880.0-E888.9, E929.3); assaults, including self-inflicted
injuries (E950.0-E969.9); combat, including blasts/explosions and
incidents related to "friendly fire" (E921.8, E922.3, E923.8,
E979.2, E985.4, E990.0-999.1); and other (all other E-codes). Respective
late effects E-codes were included in each category. In cases where more
than one source of injury was E-coded by GS (n = 3) or VHA (n = 43)
coders, we considered the record a match if either injury source was the
same.

Analyses

We conducted descriptive analyses to characterize the study
population and injury characteristics. VHA E-coding accuracy was
examined at two levels. First, we examined accuracy in E-coding practice
(i.e., whether records had VHA E-codes when patients had externally
caused injuries or, conversely, whether records did not have VHA E-codes
when patients did not have externally caused injuries). Second, for
records determined by GS coders to be related to externally caused
injuries, we examined accuracy in source-of-injury E-coding within the
collapsed categories. Because VHA E-coding was incomplete, we also
examined accuracy of assigned E-codes by restricting analyses to the
injured patients who had been assigned an E-code by VHA coders.

We estimated accuracy by computing the following statistics: (1)
concordance, a measure of the overall accuracy in detecting the presence
or absence of a condition (e.g., presence/absence of an externally
caused injury, presence/absence of a specified source of injury); (2)
sensitivity, a measure of the accuracy of detecting the presence of a
condition; and (3) specificity, a measure of the accuracy of detecting
the absence of a condition. We computed 95 percent confidence intervals
(CIs) for each measure by using generalized estimating equations to more
accurately reflect any variation due to the correlation of outcomes
within PRC sites and, consequently, to safeguard against misleadingly
narrow CIs by not accounting for such variation [26]. Accuracy was
examined by PRC site, year of patient admission, and source-of-injury
category.

RESULTS

Patient and Injury Characteristics

A summary of patient and injury characteristics is presented in
Table 1. Of the 566 patients treated at a VHA PRC during the study time
period, the majority (n = 517; 91%) received treatment for externally
caused injuries or their late effects/sequelae. Patients without
externally caused injuries received treatment primarily for stroke,
meningitis, or cardiac arrest leading to acquired brain injury. Of the
517 injured patients, 54 percent had sustained motor vehicle-related
injuries while another 28 percent sustained injuries due to combat. A
substantial proportion of patients (n = 183; 35%) were injured during
OIF/OEF deployments. The most frequent sources of deployment-related
injuries were combat operations such as blasts/explosions (79%) followed
by motor vehicles (15%). Of the remaining patients with injuries not
related to OIF/OEF deployments (n = 334; 65%), the most frequent sources
of injuries were motor vehicles (74%), falls (9%), and assaults (8%).

E-coding Practice

Statistics estimating accuracy in VHA E-coding practice are
presented in Table 2. Overall concordance between GS and VHA coders was
75 percent. Among the 517 patients who were treated for externally
caused injuries, only 382 had been assigned E-codes by VHA coders (VHA
E-codes); thus, the sensitivity of VHA E-codes to detect injury-related
discharges in these data was 74 percent. There was a wide and
statistically significant variation in sensitivity of VHA E-codes across
facilities (p < 0.001). For example, VHA coders at Site 2 assigned
E-codes to only 59 percent of those treated for injuries, while at Site
3, coders assigned E-codes to 91 percent of patients treated for
injuries. Among the 49 PRC patients who were not treated for externally
caused injuries, only 4 had been assigned E-codes by VHA coders,
resulting in a high specificity of 92 percent. These VHA E-codes had
been incorrectly assigned to patients who, for example, experienced
cardiac arrest after overexertion (e.g., during training) or who fell
subsequent to a cardiac event but did not receive treatment for a
fall-related injury.

Source-of-Injury E-coding

Overall concordance between GS and VHA coders in determining which
discharge records should be E-coded and in assigning the same
source-of-injury category was 70 percent (95% CI: 60%-79%; data not
shown). Concordance varied significantly across sites (range: 57%-84%; p
< 0.001). There was indication of improvement in E-coding accuracy
over time, though this finding was not statistically significant (p =
0.096). Compared with data from 2001 through 2004 (concordance: 65%; 95%
CI: 51%-77%), a 20 percent increase in concordance existed between GS
and VHA E-codes in data from 2005 to 2006 (78%; 95% CI: 65%-87%). E-code
accuracy also markedly improved when analyses were restricted to the 382
injured patients for whom VHA coders had assigned an E-code. Concordance
between GS and VHA coders in assigning an E-code from the same
source-of-injury category to these discharge records was 91 percent (95%
CI: 90%-93%); concordance was uniform across sites (range: 90%-93%; p =
0.73).

Levels of sensitivity of VHA E-codes in detecting injuries
associated with motor vehicles, falls, assaults, and combat are
presented in Table 3. Across all sites combined, the sensitivity to
detect specific sources of injury was highest for injuries related to
combat (81%). Sensitivity was uniformly lower for injuries associated
with falls (60%), motor vehicles (66%), and assaults (67%). Sensitivity
to detect motor vehicle-related injuries varied significantly across
sites, ranging from 55 percent at Site 2 to 87 percent at Site 3 (p <
0.001). When these analyses were restricted to include only the injured
patients for whom VHA coders had assigned E-codes, sensitivity increased
significantly (p < 0.001 for all categories; data not shown). Across
all sites combined, VHA E-codes could detect injuries related to combat
with a sensitivity of 95 percent (95% CI: 90% 98%); falls, 88 percent
(95% CI: 87%-88%); motor vehicles, 92 percent (95% CI: 90%-94%); and
assaults, 95 percent (95% CI: 92%-97%).

DISCUSSION

Although preliminary, these results indicate that E-codes may not
be a valid source of injury etiology data for VHA rehabilitation
inpatients at this time. We found E-codes to be missing for
approximately one-fourth of polytrauma inpatients treated for injury. We
also found evidence of systematic misclassification based on source of
injury. If E-codes alone had been used to ascertain source-of-injury
information for this patient population, the proportion of injuries
associated with combat would be overestimated, while the proportions due
to falls, motor vehicles, and assaults would be underestimated. However,
deficiencies in E-coding accuracy were related more to missing E-codes
than to selection of incorrect E-codes, at least when examined by broad
source-of-injury categories.

The rate of E-coding in this study population (74%) is lower than
the average rates observed in national inpatient datasets. Coben et al.
found that 86 percent of injury records in the Healthcare Cost and
Utilization Project National Inpatient Sample were E-coded, while 87
percent across Statewide Inpatient Databases were E-coded [17]. Notable
variation in E-code completeness has been observed across individual
state systems (50%-100%) [16-17]. This variance has been associated with
the presence and enforcement of state mandates for E-code collection as
well as with the design of the discharge data system in which diagnosis
and E-codes are entered (e.g., number of available coding fields and
presence of fields dedicated for E-codes) [17]. We observed significant
variation in E-coding accuracy across the PRC facilities, which are
located in four different states. However, patterns of variation were
not consistent with the patterns observed in the same states in previous
studies. For example, Site 2, which had the lowest rate of E-coding, is
located in a state that had nearly perfect rates of E-coding in state
hospital discharge data [16]. That patterns would not be consistent
between different healthcare systems located in the same states suggests
that E-coding awareness has less to do with training required for
medical records coding certification and more to do with site policies
and practices.

Incomplete E-coding can be due to several factors. Missing E-codes
could result from insufficient injury-related details in patients'
medical records. Previous research has found that medical records with
fewer details were least likely to be E-coded and that coders believed
better clinical documentation would improve E-coding rates [18,27-28].
In this patient population, we found sufficient information in most
medical records to assign at least a nonspecific E-code capturing the
broad source of injury (e.g., E819.x: motor vehicle traffic accident of
unspecified nature). Therefore, lack of documentation is not a likely
reason for the deficiencies in E-coding we observed.

A more likely reason for the observed incomplete E-coding involves
systems issues, such as insufficiencies in the electronic system in
which VHA coders enter diagnosis and E-codes. Coders have only 13 fields
in which they can enter ICD-9-CM diagnosis codes other than the
principal diagnosis code. E-codes must also be entered in these fields.
It was not unusual for these polytrauma patients to be assigned numerous
diagnosis codes reflecting their traumatic injuries and related
comorbidities. Diagnosis codes take precedence over supplemental E-codes
because they are linked to reimbursement [29]. Future research involving
VHA medical records technicians and examining reasons for incomplete
E-coding would be informative for quality improvement efforts. To date,
research has endorsed training and incorporation of supplemental data
fields specific to E-codes as methods of improving completeness [16-17].
The VHA should consider these mechanisms to enhance E-coding accuracy.
Our findings suggest that some sites might need more attention than
others.

We observed E-codes to be relatively accurate for identifying broad
source-of-injury categories when VHA coders had assigned E-codes. We
also found that VHA coders were more likely to assign E-codes correctly
to injuries related to combat than to injuries related to other sources.
Past studies have noted similar variation in E-coding accuracy by injury
etiology [18,20,25]. In the VHA setting, this finding might reflect
heightened awareness of combat-related injuries, given the political
context in which these cases are occurring and receiving treatment.
Note, however, that the majority (54%) of PRC patients were treated for
injuries associated with motor vehicles, most of which occurred
postdeployment. The Department of Veterans Affairs (VA) has recently
shown increased interest in studying motor vehicle crashes among
veterans [30]. Emphasis throughout the VHA on the preventability and
gravity of all injuries, particularly those related to motor vehicles,
might eventually lead to improved E-coding of injuries incurred outside
of combat operations.

The VHA has been involved in initiatives to improve coding for
combat-related injuries and, specifically, coding related to TBI [31].
Considerable interest exists in tracking long-term outcomes in veterans
who sustained blast-related TBI [32]. While it is unclear in the
ICD-9-CM coding guidelines at what point symptoms due to an injury
should be considered "sequelae/late effects," a late effects
E-code appeared appropriate for a number of polytrauma inpatients. We
note that the details pertaining to injury sources and circumstances are
lost when late effects E-codes are assigned. For example, only one late
effects E-code exists for use with all injuries that are due to war
operations (E999.0). Thus, distinguishing blast-related injuries from
other combat-related injuries is not possible when late effects E-codes
are used.

The VHA will transition from the ICD-9-CM to the ICD-10th
Revision-Clinical Modification (ICD-10-CM) system of coding by 2013
[33]. The ICD-10-CM contains substantially more codes than the ICD-9-CM,
including E-codes [34]. E-codes are also built into the main coding
structure of the ICD-10-CM rather than appearing as a separate,
supplemental series of codes [34-35]. The VHA's transition to the
ICD-10-CM and any related dissemination and training efforts provide a
good window of opportunity to enhance E-coding awareness,
standardization, and accuracy. Research-based knowledge of systematic
coding inaccuracies could be used to guide these efforts.

LIMITATIONS

This study has several limitations. First, we collapsed E-codes
across broad source-of-injury categories. This approach has been
followed in other E-codes studies [18,20,23] but overestimates accuracy
of E-coding. Additionally, in cases where multiple E-codes had been
assigned by either GS or VHA coders, we declared a match if either of
the GS or VHA E-codes were the same. Therefore, our results pertaining
to source-of-injury E-coding likely overestimated the accuracy of
E-codes in detecting injury sources. Further work should be conducted to
examine precision across categories in greater detail. Second, E-codes
assigned by the study team for research purposes may not have been a
perfect GS by which to compare VHA E-codes. However, we considered this
a reasonable approach, given that our team included a certified medical
records coder, had E-coding expertise, focused solely on assigning
E-codes, had ample time per record to review and select the most
appropriate codes, and cross-validated selected codes through discussion
and consensus. Finally, practice and accuracy of E-coding for the
population of rehabilitation inpatients we analyzed may not represent
E-coding across a wider VHA inpatient population. Our study should serve
as a basis for further, more comprehensive E-coding research on the
universe of VHA inpatients treated for injury.

CONCLUSIONS

In addition to polytrauma, the VHA treats eligible veterans with a
broad range of injuries incurred during and after military service. The
systematic collection of data on injuries treated within VHA, including
their causes, mechanisms, and circumstances, would benefit
epidemiologic, health services, and rehabilitation research. Injury
research is crucial not only for enhancement of clinical services
offered to injured veterans but also for development of prevention
strategies that are both appropriate and effective. E-codes may not be a
valid source of data for injury surveillance at this time. However, with
enhanced training and policies relevant to E-coding, the VHA could
potentially ensure more widespread, standardized use and accuracy of
E-codes.

Financial Disclosures: The authors have declared that no competing
interests exist.

Funding/Support: This material was based on work supported by
research and training grants from VA Health Services Research and
Development (HSR&D) Service (grants RRP 06-150, TPP 67-005, and CDA
08-025), a locally-initiated project grant from the VA HSR&D Service
Center for Chronic Disease Outcomes Research (LIP 67-032), and support
from the HSR&D Service Polytrauma and Blast-Related Injuries Quality
Enhancement Research Initiative.

Additional Contributions: We acknowledge the veterans of OIF/OEF
and their families for their service to our country. The opinions
expressed in this study do not necessarily represent those of the VA.
Dr. Carlson is now with the Portland Center for the Study of Chronic,
Comorbid Mental and Physical Disorders, Portland VA Medical Center.

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battle and for his widow and his orphan" (Abraham Lincoln): The
Department of Veterans Affairs polytrauma system of care. Arch Phys Med
Rehabil. 2008;89(1):160-62. [PMID: 18164348]
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2005.

[29.] Rice DP, MacKenzie EJ; Centers for Disease Control (U.S.);
United States National Highway Traffic Safety Administration; Johns
Hopkins University Injury Prevention Center; University of California,
San Francisco Institute for Health & Aging. Cost of injury in the
United States: A report to Congress, 1989. San Francisco (CA): Institute
for Health & Aging, University of California, and Injury Prevention
Center, The Johns Hopkins University; San Francisco; 1989.